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The Experts below are selected from a list of 426837 Experts worldwide ranked by ideXlab platform

Shan-chwen Chang - One of the best experts on this subject based on the ideXlab platform.

Meng-shuian Hsu - One of the best experts on this subject based on the ideXlab platform.

Jongmin Lee - One of the best experts on this subject based on the ideXlab platform.

  • prediction for human intelligence using morphometric characteristics of cortical surface partial least Square Analysis
    Neuroscience, 2013
    Co-Authors: Jinju Yang, U Yoon, Hyuk Jin Yun, Y Y Choi, K H Lee, Hyunjin Park, M Hough, Jongmin Lee
    Abstract:

    Abstract A number of imaging studies have reported neuroanatomical correlates of human intelligence with various morphological characteristics of the cerebral cortex. However, it is not yet clear whether these morphological properties of the cerebral cortex account for human intelligence. We assumed that the complex structure of the cerebral cortex could be explained effectively considering cortical thickness, surface area, sulcal depth and absolute mean curvature together. In 78 young healthy adults (age range: 17–27, male/female: 39/39), we used the full-scale intelligence quotient (FSIQ) and the cortical measurements calculated in native space from each subject to determine how much combining various cortical measures explained human intelligence. Since each cortical measure is thought to be not independent but highly inter-related, we applied partial least Square (PLS) regression, which is one of the most promising multivariate Analysis approaches, to overcome multicollinearity among cortical measures. Our results showed that 30% of FSIQ was explained by the first latent variable extracted from PLS regression Analysis. Although it is difficult to relate the first derived latent variable with specific anatomy, we found that cortical thickness measures had a substantial impact on the PLS model supporting the most significant factor accounting for FSIQ. Our results presented here strongly suggest that the new predictor combining different morphometric properties of complex cortical structure is well suited for predicting human intelligence.

Hao Lixia - One of the best experts on this subject based on the ideXlab platform.

Renliang Huang - One of the best experts on this subject based on the ideXlab platform.

  • understanding the key factors for enzymatic conversion of pretreated lignocellulose by partial least Square Analysis
    Biotechnology Progress, 2009
    Co-Authors: Renliang Huang
    Abstract:

    The relationship between the physicochemical properties of lignocellulosic substrates and enzyme digestion is still not well known. After different pretreatments, cellulase hydrolysis and measurements of physicochemical characteristics by column solute exclusion, particle size Analysis, X-ray diffraction, Fourier transform infrared spectroscopy and solid state 13C nuclear magnetic resonance were performed in this study. Partial least Squares was then applied to seek the key factors limiting the rate and extent of cellulose digestion. According to the PLS results, the most important factor for cellulose digestion was accessible interior surface area, followed by delignification and the destruction of the hydrogen bonds. The cellulose digestion at 2 and 24 hr were improved with the increased accessibility of interior surface area to the reporter molecules of 5.1-nm diameter. Removal of lignin and breaking of hydrogen bonds were also found to significantly promote cellulose conversion. Other properties, including the breakdown of intramolecular hydrogen bonds, cellulose crystallinity, and hemicellulose content, had less effect on the efficiency of enzymatic hydrolysis. © 2009 American Institute of Chemical Engineers Biotechnol. Prog., 2010